Software Engineer/ ML Engineer

Be part of something revolutionary

At o9 Solutions, our mission is clear: be the Most Valuable Platform (MVP) for enterprises. With our AI-driven platform — the o9 Digital Brain — we integrate global enterprises’ siloed planning capabilities, helping them capture millions and, in some cases, billions of dollars in value leakage. But our impact doesn’t stop there. Businesses that plan better and faster also reduce waste, which drives better outcomes for the planet, too.

We're on the lookout for the brightest, most committed individuals to join us on our mission. Along the journey, we’ll provide you with a nurturing environment where you can be part of something truly extraordinary and make a real difference for companies and the planet.
 

Machine Learning Engineer

About the role

We are looking for a highly skilled Machine Learning Engineer between 1 to 5 years of working experience with strong programming expertise, a fundamental understanding of MLOps principles, and experience designing scalable, production-ready ML systems.

In this role, you will be responsible for building robust machine learning models, streamlining MLOps workflows, and optimizing performance across the entire ML lifecycle. A key focus will be on Python package development and ensuring integration of ML models into production.

What will you do:

Software Engineering & Architecture:

• Write clean, modular, and efficient object-oriented Python code following best practices.

• Develop, maintain, and release internal Python packages for ML operations.

• Evaluate and design scalable ML system architectures, balancing performance, maintainability, and scalability.

• Refactor and optimize existing codebases for scalability and performance.

• Follow Git workflow best practices, implement testing strategies, and ensure long-term code maintainability.

Machine Learning Development:

• Apply a strong understanding of machine learning algorithms, especially tree-based models (e.g., LightGBM) to build time-series forecasting models.

• Design machine learning systems that are scalable and efficient.

• Engineer and optimize high-quality features for ML pipelines.

• Conduct model evaluation and tuning to improve performance.

MLOps:

• Build and maintain CI/CD pipelines for ML models and Python package releases.

• Design and build scalable data pipelines for  ingestion and transformation while ensuring data quality, consistency, and efficiency.

• Deploy and serve models for batch and real-time inference (FastAPI, Flask).

Infrastructure & Cloud Computing:

• Utilize Docker and Kubernetes to containerize and orchestrate machine learning workloads.

• Optimize resource allocation for large-scale ML training and inference.

Collaboration & Mentorship:

• Work closely with data scientists to integrate ML models into production.

• Contribute to internal ML documentation and knowledge-sharing sessions.

• Conduct code reviews and technical mentorship to other junior engineers.

• Lead best practices in code quality, testing, and ML governance.

What should you have:

• Experience: 1 to 5 years in Machine Learning, Software Engineering, or related fields.

• Education: Bachelor’s or Master’s degree in Computer Science, AI/ML, or equivalent.

• Programming: Expert-level proficiency in Python, with strong coding skills.

• Machine Learning Algorithms: Fundamental understanding of various machine learning algorithms, including supervised and unsupervised techniques.

• MLOps: Good to have Hands-on experience with data pipelines, training/inference, deployment (batch/real-time), model retraining, testing (e.g. unit, regression), and version control.

• Infrastructure: Exposure/ Experience with Docker.

• Version Control & Collaboration: Exposure/ Experience with Git and Agile methodologies (e.g. Jira / Azure DevOps).

Preferred Qualifications:

• Time-Series Forecasting: Experience in designing and implementing time-series forecasting models.

• Open-Source Contributions: Experience in developing, maintaining, or contributing to open-source libraries.

• Model Explainability: Hands-on experience with SHAP or LIME for interpretability.

• CI/CD: Experience with CI/CD tools (GitHub Actions, Azure DevOps).

• Model Deployment: Knowledge about deploying models via REST APIs, Flask, or FastAPI.

• Real-Time Machine Learning: Knowledge of low-latency ML systems.

Why Join Us?

• Work on cutting-edge ML problems in a fast-paced environment.

• Opportunity to shape the MLOps ecosystem within the company.

• A global and open culture of innovation, collaboration, and continuous learning.

If you are passionate about building robust, scalable ML solutions and want to be part of a forward-thinking team, we encourage you to apply!

More about us… 

With the latest increase in our valuation from $2.7B to $3.7B despite challenging global macroeconomic conditions, o9 Solutions is one of the fastest-growing technology companies in the world today. Our mission is to digitally transform planning and decision-making for the enterprise and the planet. Our culture is high-energy and drives us to aim 10x in everything we do.

Our platform, the o9 Digital Brain, is the premier AI-powered, cloud-native platform driving the digital transformations of major global enterprises including Google, Walmart, ABInBev, Starbucks and many others.

Our headquarters are located in Dallas, with offices in Amsterdam, Paris, London, Barcelona, Madrid, Sao Paolo, Bengaluru, Tokyo, Seoul, Milan, Stockholm, Sydney, Shanghai, Singapore Munich, Toronto.

o9 is an equal opportunity employer and seeks applicants of diverse backgrounds and hires without regard to race, colour, gender, religion, national origin, citizenship, age, sexual orientation or any other characteristic protected by law.